Senior Machine Learning Applied Scientist - Video Shopping
- Palo Alto, CA
Help create the future of Video Shopping with Amazon! It's an exciting time to be on the Video Shopping team. Amazon's Video Shopping team has a problem: We have millions of videos that help millions of customers shop every day. These include product demos, customer reviews, buying guides, how-to's, and others. How do we choose the right videos to show to the right customers at the right time, to help them make the right shopping decision? That's where you come in.
We need a Senior Applied Scientist with experience in Machine Learning, Big Data, and Service Oriented Architecture, to be part of a team of talented engineers and scientists to solve this problem. As an Applied Scientist on the VSE's Ranking and Relevance team, you will build systems for cataloging, analyzing, ranking, and vending shopping related videos across Amazon. You will leverage your expertise to work with your team to deliver solutions at Amazon scale.
The ideal candidate will have hands-on experience as well as be able to make the right decisions about technology, models and methodology choices. You will strive for simplicity, and demonstrate significant creativity and high judgment backed by statistical proof.
This position in the Video Shopping Experience team presents a unique and rare opportunity to get in on the ground floor within a fast growing business and help shape the technology, product and the business.
We're looking for senior scientist capable of using machine learning and statistical techniques to create state-of-the-art solutions for non-trivial, and arguably, unsolved problems. If you are results driven, interested in how to apply advanced Machine Learning techniques, love to work with video, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.
• Use statistical and machine learning techniques to create scalable solutions for video analysis and content moderation problems
• Analyze and extract information from large amounts of videos to help moderate and optimize search across videos
• Work closely with software engineering teams to drive real-time model implementations and new feature creations
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Demonstrated ability to drive adoption of best practices across organizations.
• Proven track record of delivering production-ready code with superior user experience.
• PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
• 3+ years of experience of building machine learning models for business application
• Experience programming in Java, C++, Python or related language
• MS in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
• 4+ years professional experience in predictive modeling and analysis
• Computer Science fundamentals in data structures, algorithm design, problem solving, and complexity analysis
• Proficiency in, at least, one modern programming language such as C, C++, Java, or Perl
• Experience with Python, R, MATLAB or similar scripting languages.
• PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field
• Significant peer reviewed scientific contributions in relevant field.
• Extensive experience applying theoretical models in an applied environment.
• Strong fundamentals in problem solving, algorithm design and complexity analysis.
• Strong personal interest in learning, researching, and creating new technologies with high commercial impact.
• Experience with defining organizational research and development practices in an industry setting.
• Experience with AWS technologies
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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